How to Bring Storytelling to Analytics

We all dread the weekly report. A spreadsheet arrives in your inbox, crammed full of numbers, perhaps a few charts, maybe even some attempts at "data visualization," but usually without any narrative or explanation. You look at it and think: "So what?" So what is it telling you and so what are you going to do about it? We're not short of numbers. We're short of understanding about what to do about the numbers. As analysts, we're complicit in this. We have a habit of sending out data rather than insights. We're good at reading numbers but not great at telling stories. We need to be telling more stories because people remember stories and they rarely remember a piece of analysis.

But what are the ingredients of a good story and how is that relevant to analysis?

Stories have a beginning, a middle, and an end. When it comes to delivering in results of a project in a presentation, I urge consultants to go by the old adage: "Tell them what you're going to tell them, tell them, and then tell them what you told them." In other words, start off by giving key highlights, tell the story, summarize, and close.

In addition to a basic structure, a story needs a good narrative. In our data-driven world it's easy to get hung up on numbers and to have slide after slide containing tables full of numbers and complex graphs. The storytelling analyst will understand the narrative and will find a way to tell the narrative in an engaging and memorable way. Often, less can be more. Fewer numbers can give greater insight if they are the right numbers. Less precision can lead to more confidence. "67.3% of visitors…" can almost appear to be too precise and can leads to challenges around data accuracy, whereas "two thirds of visitors…" takes the data issues away and the focus is then on what the two-thirds of visitors did or didn't do or think.

The storytelling analyst will also develop the flow. Stories have a cause-and-effect relationship. There are events and then there are consequences. Otherwise, the narrative is just a series of events and there is nothing for the listener or the reader to take away. In the book, "Elements of Persuasion," Richard Maxwell and Robert Dickman define the elements of a good story as:

The passion with which the story is told

A hero to drive the action

An obstacle or an antagonist to challenge the hero

A moment of awareness where the hero realizes how he can overcome the obstacle

A transformation in the hero and the world around him

It can be difficult at first take to see how these elements might be incorporated into the delivery of a piece of business analysis or research, but it's worth thinking about it. Passion is possibly the easiest in a way. A good analyst will be interested in the business and will have empathy for it. He will understand the consequences of the events that he's describing and the relevance of them to the audience.

The story's hero could be business customers or a segment of them. One technique might be even to personalize the story around an individual or groups of individuals by using pen portraits or personas. This can help bring the story to life and increase its relevance. The obstacle that the hero needs to overcome would be the point of the research or the analysis. The moment of awareness would be the insight from the research and the transformation would be the consequences from the recommendations accompanying the analysis.

So, next time you send out the weekly report or deliver analysis, ask yourself "What's the story here?"

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ABOUT THE AUTHOR

Neil Mason is SVP, Customer Engagement at iJento. He is responsible for providing iJento clients with the most valuable customer insights and business benefits from iJento's digital and multichannel customer intelligence solutions.

Neil has been at the forefront of marketing analytics for over 25 years. Prior to joining iJento, Neil was Consultancy Director at Foviance, the UK's leading user experience and analytics consultancy, heading up the user experience design, research, and digital analytics practices. For the last 12 years Neil has worked predominantly in digital channels both as a marketer and as a consultant, combining a strong blend of commercial and technical understanding in the application of consumer insight to help major brands improve digital marketing performance. During this time he also served as a Director of the Web Analytics Association (DAA) for two years and currently serves as a Director Emeritus of the DAA. Neil is also a frequent speaker at conferences and events.

Neil's expertise ranges from advanced analytical techniques such as segmentation, predictive analytics, and modelling through to quantitative and qualitative customer research. Neil has a BA in Engineering from Cambridge University and an MBA and a postgraduate diploma in business and economic forecasting.

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